Estimating effective density of cohesive sediment using shape factors from holographic images

Choi, Sun Min; Seo, Jun Young; Ha, Ho Kyung; Lee, Guan‐hong

doi:10.1016/j.ecss.2018.10.008

Cited by 6 publications

(5 citation statements)

References 42 publications

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“…The particle density can be estimated from the solidity calculated by the LISST-HOLO software. The solidity is defined as the solid fraction of a given particle, and can be related to the porosity of that particle (Choi et al, 2018). A fully solid particle will have a solidity of 1, whereas a solidity close to 0 will indicate a very porous particle.…”

Section: Lisst-holomentioning

confidence: 99%

Characterization and classification of estuarine suspended particles based on their inorganic/organic matter composition

Safar

Chassagne²,

Rijnsburger³

et al. 2022

Front. Mar. Sci.

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An 11 hours survey was performed on the 17th of September 2014 in the Rhine Region Of Freshwater Influence (Rhine-ROFI) about 10 km downstream of the mouth of the Rotterdam Waterway during calm weather conditions. Suspended Particle Matter (SPM) measurements were performed during a full tidal cycle, near the seabed, at neap tide, and samples were taken at 0.6 meter above bed for on-board analysis. The measurements were performed with (a) LISST 100X, a submersible particle size analyzer, (b) LISST-HOLO, a submersible digital holographic camera, (c) a home-made underwater camera and (d) an on-board LabSFLOC2 video microscopy equipment that used in-situ collected samples. The first aim of the present study was to compare the results obtained from the different monitoring techniques and to characterize the different types of suspended particles found in-situ. It was found that that the highly anisotropic particles present in the water column lead to multiple peaks in the Particle Size Distributions (PSD) found using the LISST 100X. Using the LISST-HOLO, underwater camera and LabSFLOC2 camera these particles could properly be imaged and meaningful PSD’s were obtained using these techniques in the size range > 20 μm. LabSFLOC2, LISST-HOLO and the underwater camera moreover provide information on the size and aspect ratio of particles. On the other hand, LISST 100X can be used to detect the fine fraction (<20 μm), a size range that is not accessible for the other techniques. From the analysis of the data on the survey day, three classes of particles were identified, based on composition rather than size (the sizes given here are purely indicative): (1) mineral (inorganic) sediment particles in the range size 5 - 20 μm, (2) organic/inorganic aggregates in the size range 20 - 200 μm and (3) organic particles in the size range > 200 μm. A large range of settling velocities (0.1 - 10 mm/s) and aspect ratios between 1 and 10 were recorded by video microscopy (LabSFLOC2). This spreading in settling velocities and aspect ratio was due to the different properties (shape, effective density and size) of the particles in the water column. The second aim of the study was to reproduce the flocs found in-situ in the lab and investigate the kinetics of flocculation between inorganic and living organic matter. Laboratory experiments were conducted with grab samples obtained from Port of Rotterdam harbour and living microalgae (Skeletonema costatum). The results of these experiments showed a shift in effective density upon addition of living algae to the sediment, which confirmed the flocculation ability between sediment and microalgae. The flocculation occured on a timescale of minutes and lead to flocs having a large spread in density for a given size, due to the heteregeous inorganic/organic composition of the flocs. This spread in density was at the origin of the large range of settling velocities for a given floc size observed in-situ, which leads to conclude that organic matter should be an important input parameter in sediment transport models.

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Section: Lisst-holomentioning

confidence: 99%

Characterization and classification of estuarine suspended particles based on their inorganic/organic matter composition

Safar

Chassagne²,

Rijnsburger³

et al. 2022

Front. Mar. Sci.

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“…Such patterns with different fringe spacings contain unique information of the phase and amplitude to deduce the size and position of suspended particles (Graham and Nimmo-Smith, 2010). The interference patterns on the hologram were reconstructed using Holo Batch R software (Sequoia Inc.) (Owen and Zozulya, 2000;Graham and Nimmo-Smith, 2010;Choi et al, 2018;Giering et al, 2020). The noise and stationary particles on the image were removed by reapplying the collimated beam to the hologram.…”

Section: Lisst-holomentioning

confidence: 99%

“…The particles located within a three-dimensional volume along the path length (typically 3-50 mm, 10 mm in this study) are shown as in-focus monochrome (binary) images with a high pixel resolution (1 pixel = 4.4 µm × 4.4 µm). Using image analysis, Euclidian and fractal geometry parameters for each binarized particle were determined as follows: perimeter (P), area (A), major (a), and minor (b) axis lengths (Olson, 2011;Choi et al, 2018;Many et al, 2019), where P is the total length surrounding the projected particle area, A is the extent converted from pixels occupied by the projected two-dimensional area of the particle, a is the axis passing through the center of the particle corresponding to the minimum rotational energy of the shape, and b is the perpendicular axis to a (Olson, 2011).…”

Section: Lisst-holomentioning

confidence: 99%

“…Since the introduction of holography into the scientific community in the 1940s (Gabor, 1948), it has become an indispensable technique used in various fields of fluid mechanics, metrology, and medical imaging (Nayak et al, 2021). Because holography is a proven method that enables the provision of a solution to the limitations of the focal plane, the marine science community has recently adopted it to collect information on the three-dimensional properties of particulate matter (e.g., sediment and plankton) suspended in a water column (e.g., Graham and Nimmo-Smith, 2010;Choi et al, 2018;Nayak et al, 2019;Giering et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Practical Method to Screen Contaminated Holograms of Flocs Using Light Intensity

et al. 2021

Self Cite

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Submergible digital holographic camera can measure the in situ size and shape of suspended particles, such as complex flocs and biological organisms, without disturbance. As the number of particles in the water column increases, overlapping concentric rings (interference patterns) can contaminate the holographic images. Using light intensity (LI), this study proposes a practical method to assess the degree of contamination and screen out contaminated images. The outcomes from image processing support that LI normalized on a gray scale of 0 (black) to 255 (white) can be a reliable criterion for defining the contamination boundary. Results found that as LI increased, the shape of the particle size distribution shifted from a positively skewed to a normal distribution. When LI was lower than approximately 80, owing to the distortion of particle properties, the settling velocities derived from the contaminated holograms with mosaic patterns were underestimated compared to those from the uncontaminated holograms. The proposed method can contribute to a more accurate estimation of the transport and behavior of cohesive sediments in shallow estuarine environments.

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“…In the governing equations for the three-dimensional transport of cohesive sediment, one of the most important parameters is the floc settling velocity [12,15,[85][86][87][88][89][90]. It depends on the floc's physical properties (size, shape, effective density, etc.)…”

Section: Application Of the Entropic Model In Engineering Practices And Its Limitationsmentioning

confidence: 99%

An Extended Entropic Model for Cohesive Sediment Flocculation in a Piecewise Varied Shear Environment

Zhu

Dou

2021

Entropy

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In this study, an extended model for describing the temporal evolution of a characteristic floc size of cohesive sediment particles when the flocculation system is subject to a piecewise varied turbulent shear rate was derived by the probability methods based on the Shannon entropy theory following Zhu (2018). This model only contained three important parameters: initial and steady-state values of floc size, and a parameter characterizing the maximum capacity for floc size increase (or decay), and it can be adopted to capture well a monotonic pattern in which floc size increases (or decays) with flocculation time. Comparison with 13 literature experimental data sets regarding floc size variation to a varied shear rate showed the validity of the entropic model with a high correlation coefficient and few errors. Furthermore, for the case of tapered shear flocculation, it was found that there was a power decay of the capacity parameter with the shear rate, which is similar to the dependence of the steady-state floc size on the shear rate. The entropic model was further parameterized by introducing these two empirical relations into it, and the finally obtained model was found to be more sensitive to two empirical coefficients that have been incorporated into the capacity parameter than those in the steady-state floc size. The proposed entropic model could have the potential, as an addition to existing flocculation models, to be coupled into present mature hydrodynamic models to model the cohesive sediment transport in estuarine and coastal regions.

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Estimating effective density of cohesive sediment using shape factors from holographic images

Cited by 6 publications

References 42 publications

Characterization and classification of estuarine suspended particles based on their inorganic/organic matter composition

Characterization and classification of estuarine suspended particles based on their inorganic/organic matter composition

Practical Method to Screen Contaminated Holograms of Flocs Using Light Intensity

An Extended Entropic Model for Cohesive Sediment Flocculation in a Piecewise Varied Shear Environment

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